Enabling Lite Members
Lite members are the Hazelcast cluster members that do not store data. These members are used mainly to execute tasks and register listeners, and they do not have partitions.
You can form your cluster to include the regular Hazelcast members to store data and
lite members to run heavy computations.
The presence of lite members does not affect the operations performed on the other members in the cluster.
You can directly submit your tasks to the lite members, register listeners on them, and invoke operations for
the Hazelcast data structures on them such as map.put()
and map.get()
.
If you want to use lite members in a Hazelcast Enterprise Edition cluster, they are also subjected to the Enterprise Edition license. |
Promoting Lite Members to Data Members
You can promote lite members to data members. This promotion rebalances the cluster partitions and reassigns the ownerships of partition portions to the newly promoted data members.
You can promote a lite member programmatically using the Cluster
interface as follows:
Config config = new Config();
config.setLiteMember(true);
HazelcastInstance hazelcastInstance = Hazelcast.newHazelcastInstance(config);
Cluster cluster = hazelcastInstance.getCluster();
cluster.promoteLocalLiteMember();
Demoting Data Members to Lite Members
You can demote data members to lite ones. Similar to the promotions, the demotion leads to performing the rebalancing and reassignment of partitions.
You can demote a data member programmatically using the Cluster
interface as follows:
Config config = new Config();
config.setLiteMember(true);
HazelcastInstance hazelcastInstance = Hazelcast.newHazelcastInstance(config);
Cluster cluster = hazelcastInstance.getCluster();
cluster.demoteLocalDataMember();
You can specify a timeout value for waiting during the data member demotion, using the hazelcast.member.demote.max.wait
property.
Default timeout value is 600 seconds. The default duration is long enough to allow for partition migrations to complete for most use cases.
You can increase or decrease this value depending on the size of your cluster.